Towards consistently measuring and monitoring habitat condition with airborne laser scanning and unmanned aerial vehicles by W. Daniel Kissling, Yifang Shi, Jinhu Wang, Agata Walicka, Charles George, Jesper E. Moeslund, France Gerard

“…A VRE would also improve data management, metadata standardization, workflow reproducibility, and transferability of structure-from-motion algorithms and machine learning models such as random forests and convolutional neural networks. …”
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Fault Diagnosis Method for Main Pump Motor Shielding Sleeve Based on Attention Mechanism and Multi-Source Data Fusion by Nengqing Liu, Xuewei Xiang, Hui Li, Zhi Chen, Peng Jiang

“…The operating environment of the shielding sleeve of the main pump motor is complex and changeable, and it is affected by various stresses; so, it is prone to bulging, cracking, and wear failure. …”
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Associations between ambient particulate matter exposure and the prevalence of arthritis: Findings from the China Health and Retirement Longitudinal Study. by Yuntian Ye, Kuizhi Ma, Aifeng Liu

“…The levels of air pollution exposure were estimated using a spatial-temporal extreme random forest model, integrating ground monitoring, remote sensing data, and model simulations, encompassing PM1, PM2.5, PM10, NH4, NO3, O3, and SO4 concentrations. …”
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Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…Background: Brain tumors present a complex challenge in clinical oncology, where precise diagnosis and classification are pivotal for effective treatment planning. …”
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Quantitative prediction of water quality in Dongjiang Lake watershed based on LUCC by Yang Song, Xiaoming Li, Ying Zheng, Gui Zhang

“…Land Use/ Cover Change (LUCC) plays a crucial role in influencing hydrological processes, nutrient cycling, and sediment transport in watersheds, ultimately impacting water quality on both spatial and temporal scales. Accurately predicting changes in watershed water quality is beneficial for the sustainable management of water resources. …”
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Mapping Crop Types and Cropping Patterns Using Multiple-Source Satellite Datasets in Subtropical Hilly and Mountainous Region of China by Yaoliang Chen, Zhiying Xu, Hongfeng Xu, Zhihong Xu, Dacheng Wang, Xiaojian Yan

“…The results suggest that the proposed method has great potential in accurately mapping crop types in a complex subtropical planting environment.…”
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Multi-scale machine learning model predicts muscle and functional disease progression by Silvia S. Blemker, Lara Riem, Olivia DuCharme, Megan Pinette, Kathryn Eve Costanzo, Emma Weatherley, Jeff Statland, Stephen J. Tapscott, Leo H. Wang, Dennis W. W. Shaw, Xing Song, Doris Leung, Seth D. Friedman

“…A three-stage random forest model was developed to predict annualized changes in muscle composition and a functional outcome (timed up-and-go (TUG)). …”
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Estimating Winter Wheat Canopy Chlorophyll Content Through the Integration of Unmanned Aerial Vehicle Spectral and Textural Insights by Huiling Miao, Rui Zhang, Zhenghua Song, Qingrui Chang

“…Finally, the optimal model was utilized for spatial mapping. The results provided the following indications: (1) Red-edge vegetation indices (RIs) and TIs were key to estimating RCCC. …”
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Effects of Parameter Uncertainties on Interaction between Submarine Telecommunication Cables and Lateral Seabed Movements by Cuiwei Fu, Xiaogang Qin, Yu Wang

“…Statistical analysis of the MCS results is performed to prioritize the effects of parameter uncertainties on cable damage probability. Random field is also used to model spatial variability of soil parameters. …”
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Study on the Dynamic Changes of Landscape Ecological Pattern in Beihai Wetland, Tengchong City by Xu Hongmei, Xi Wujun

“…Applying a hybrid Maximum Likelihood Classification (MLC) and Random Forest (RF) method, it extracted spatial distribution data for Tengchong’s Beihai Wetland across five phases (2009–2024) and analyzed landscape pattern spatiotemporal changes. …”
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A study on forest fire risk assessment in jiangxi province based on machine learning and geostatistics by Jinping Lu, Mangen Li, Yaozu Qin, Niannan Chen, Lili Wang, Wanzhen Yang, Yuke Song, Yisu Zheng

“…WoE was employed to select negative samples, which were compared with those obtained using traditional random sampling methods. The optimal model was then utilized to generate seasonal spatial distribution maps of forest fire risk throughout Jiangxi Province. …”
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Reveal the mechanism of brain function with fluorescence microscopy at single-cell resolution: from neural decoding to encoding by Kangchen Li, Huanwei Liang, Jialing Qiu, Xulan Zhang, Bobo Cai, Depeng Wang, Diming Zhang, Bingzhi Lin, Haijun Han, Geng Yang, Zhijing Zhu

“…While neural decoding aims to establish an interpretable theory of how complex biological behaviors are represented in neural activities, neural encoding focuses on manipulating behaviors through the stimulation of specific neurons. …”
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Estimation of Moderate-Resolution Snow Depth in Xinjiang With Enhanced-Resolution Passive Microwave and Reanalysis Data by Machine Learning Methods by Yongchang Yan, Yan Qin, Yongqiang Liu, Yubao Qiu, Yang Liu

“…However, the exiting SD retrieval algorithms overlook the impact of snow characteristics on brightness temperature, leading to inadequate representation of SD in complex regions. Therefore, this study constructs and optimizes SD retrieval models using four machine learning algorithms, including extreme gradient boosting (XGBoost), light gradient-boosting machine (LightGBM), categorical boosting (CatBoost), and random forest (RF) combing enhanced-resolution passive microwave data. …”
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Advances in non-invasive brain stimulation: enhancing sports performance function and insights into exercise science by Shuo Qi, Jinglun Yu, Li Li, Chen Dong, Zhe Ji, Lei Cao, Zhen Wei, Zhiqiang Liang

“…The cerebral cortex, as the pinnacle of human complexity, poses formidable challenges to contemporary neuroscience. …”
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An Improved U-Net-Based Framework for Estimating River Surface Flow Velocity by 周继威, 安国成, 王根一

“…Larger crops (640 pixels) preserved spatial context, achieving MAVD=0.862 and FRA=0.927, whereas smaller crops (160 pixels) limited velocity detection to 1.5 m/s, inadequate for high-flow scenarios (>3 m/s). …”
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Comparative analysis of deep neural network architectures for renewable energy forecasting: enhancing accuracy with meteorological and time-based features by Sunawar Khan, Tehseen Mazhar, Muhammad Amir Khan, Tariq Shahzad, Wasim Ahmad, Afsha Bibi, Mamoon M. Saeed, Habib Hamam

“…Conversely, traditional models demonstrated a reliable albeit less dynamic ability to elucidate the complexities of renewable energy data; for instance, Random Forest exhibited a mean squared error (MSE) of 0.025, while Support Vector Regression (SVR) recorded an MSE of 0.030. …”
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Neutral Protamine Hagedorn (NPH) insulin attenuates memory impairments in diabetic rats by Marcelo T. Andrade, Camila B. Gomes, Débora O. Fernandes, Bruno P. Melo, Michele M. Moraes, Ana F. S. Almeida, Laura F. J. Alvarado, Grace S. Pereira, Juliana B. Guimarães, Elsa Heyman, Romain Meeusen, Thiago T. Mendes, Danusa D. Soares

“…However, despite treatment, T1DSTZ rats still exhibited memory impairments, highlighting the complexity of diabetes-associated cognitive decline. …”
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Profiling students’ multiple intelligences approach in the learning of economics in a Ghanaian University by Ernest Opoku, Dominic Owusu, Francis Arthur, Iddrisu Salifu, Emmanuel Quayson, Eric Boateng, Francis Obeng Gyedu, Stanley Asare-Bediako, Emmanuel Rungson Attom, Solomon Adjatey Tetteh, Sharon Abam Nortey, Ayishatu Ameen

“…Abstract The evolving landscape of higher education requires a better understanding of students’ cognitive strengths, especially in complex disciplines such as Economics where multiple approaches to problem solving are essential. …”
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Multi-modal remote sensory learning for multi-objects over autonomous devices by Aysha Naseer, Naif Almudawi, Hanan Aljuaid, Abdulwahab Alazeb, Yahay AlQahtani, Asaad Algarni, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…During the labeling step, the use of MRF guarantees precise spatial contextual modeling, which improves comprehension of intricate interactions between nearby aerial objects. …”
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Urban morphology impacts on urban microclimate using artificial intelligence – a review by Ahmed Marey, Jiwei Zou, Sherif Goubran, Liangzhu Leon Wang, Abhishek Gaur

“…Urban morphology, defined by the characteristics and spatial arrangement of urban structures, significantly affects urban microclimate in terms of thermal environments, wind dynamics, energy use, and outdoor air quality. …”
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